{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "weights = torch.load(\"../experiments/202011200421/save_40.pth\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['epoch', 'optimizer_global', 'arch', 'optimizer_fusion', 'state_dict', 'optimizer_sound'])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'resnet-50'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights['arch']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "module.fuse.weight\n",
      "module.fuse.bias\n",
      "module.fuseav.weight\n",
      "module.fuseav.bias\n",
      "module.fusion3.affine_rgb.weight\n",
      "module.fusion3.affine_rgb.bias\n",
      "module.fusion3.affine_audio.weight\n",
      "module.fusion3.affine_audio.bias\n",
      "module.fusion3.w_a_rgb.weight\n",
      "module.fusion3.w_a_rgb.bias\n"
     ]
    }
   ],
   "source": [
    "path = \"../experiments/202011200247/save_40.pth\"\n",
    "weights = torch.load(path)\n",
    "del_dicts = ['fusion3', 'fuse']\n",
    "weight_keys = list(weights['state_dict'].keys())\n",
    "model_weight = weights['state_dict']\n",
    "for key in weight_keys:\n",
    "    for del_key in del_dicts:\n",
    "        if del_key in key:\n",
    "            print(key)\n",
    "            del model_weight[key]\n",
    "weights['state_dict'] = model_weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "../experiments/202011200247/save_40_WoFuse.pth\n"
     ]
    }
   ],
   "source": [
    "dirname = os.path.dirname(path)\n",
    "basename = os.path.basename(path)\n",
    "dst_name = os.path.join(dirname, basename.split(\".\")[0] + \"_WoFuse.pth\")\n",
    "print(dst_name)\n",
    "torch.save(weights, dst_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['module.conv1.weight',\n",
       " 'module.bn1.weight',\n",
       " 'module.bn1.bias',\n",
       " 'module.bn1.running_mean',\n",
       " 'module.bn1.running_var',\n",
       " 'module.bn1.num_batches_tracked',\n",
       " 'module.layer1.0.conv1.weight',\n",
       " 'module.layer1.0.bn1.weight',\n",
       " 'module.layer1.0.bn1.bias',\n",
       " 'module.layer1.0.bn1.running_mean',\n",
       " 'module.layer1.0.bn1.running_var',\n",
       " 'module.layer1.0.bn1.num_batches_tracked',\n",
       " 'module.layer1.0.conv2.weight',\n",
       " 'module.layer1.0.bn2.weight',\n",
       " 'module.layer1.0.bn2.bias',\n",
       " 'module.layer1.0.bn2.running_mean',\n",
       " 'module.layer1.0.bn2.running_var',\n",
       " 'module.layer1.0.bn2.num_batches_tracked',\n",
       " 'module.layer1.0.conv3.weight',\n",
       " 'module.layer1.0.bn3.weight',\n",
       " 'module.layer1.0.bn3.bias',\n",
       " 'module.layer1.0.bn3.running_mean',\n",
       " 'module.layer1.0.bn3.running_var',\n",
       " 'module.layer1.0.bn3.num_batches_tracked',\n",
       " 'module.layer1.0.downsample.0.weight',\n",
       " 'module.layer1.0.downsample.1.weight',\n",
       " 'module.layer1.0.downsample.1.bias',\n",
       " 'module.layer1.0.downsample.1.running_mean',\n",
       " 'module.layer1.0.downsample.1.running_var',\n",
       " 'module.layer1.0.downsample.1.num_batches_tracked',\n",
       " 'module.layer1.1.conv1.weight',\n",
       " 'module.layer1.1.bn1.weight',\n",
       " 'module.layer1.1.bn1.bias',\n",
       " 'module.layer1.1.bn1.running_mean',\n",
       " 'module.layer1.1.bn1.running_var',\n",
       " 'module.layer1.1.bn1.num_batches_tracked',\n",
       " 'module.layer1.1.conv2.weight',\n",
       " 'module.layer1.1.bn2.weight',\n",
       " 'module.layer1.1.bn2.bias',\n",
       " 'module.layer1.1.bn2.running_mean',\n",
       " 'module.layer1.1.bn2.running_var',\n",
       " 'module.layer1.1.bn2.num_batches_tracked',\n",
       " 'module.layer1.1.conv3.weight',\n",
       " 'module.layer1.1.bn3.weight',\n",
       " 'module.layer1.1.bn3.bias',\n",
       " 'module.layer1.1.bn3.running_mean',\n",
       " 'module.layer1.1.bn3.running_var',\n",
       " 'module.layer1.1.bn3.num_batches_tracked',\n",
       " 'module.layer1.2.conv1.weight',\n",
       " 'module.layer1.2.bn1.weight',\n",
       " 'module.layer1.2.bn1.bias',\n",
       " 'module.layer1.2.bn1.running_mean',\n",
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       " 'module.layer1.2.bn1.num_batches_tracked',\n",
       " 'module.layer1.2.conv2.weight',\n",
       " 'module.layer1.2.bn2.weight',\n",
       " 'module.layer1.2.bn2.bias',\n",
       " 'module.layer1.2.bn2.running_mean',\n",
       " 'module.layer1.2.bn2.running_var',\n",
       " 'module.layer1.2.bn2.num_batches_tracked',\n",
       " 'module.layer1.2.conv3.weight',\n",
       " 'module.layer1.2.bn3.weight',\n",
       " 'module.layer1.2.bn3.bias',\n",
       " 'module.layer1.2.bn3.running_mean',\n",
       " 'module.layer1.2.bn3.running_var',\n",
       " 'module.layer1.2.bn3.num_batches_tracked',\n",
       " 'module.layer2.0.conv1.weight',\n",
       " 'module.layer2.0.bn1.weight',\n",
       " 'module.layer2.0.bn1.bias',\n",
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       " 'module.layer2.0.bn1.num_batches_tracked',\n",
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       " 'module.layer2.0.bn3.weight',\n",
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       " 'module.layer2.0.bn3.num_batches_tracked',\n",
       " 'module.layer2.0.downsample.0.weight',\n",
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       " 'module.layer2.2.bn3.weight',\n",
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       " 'module.layer2.3.bn1.weight',\n",
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       " 'module.layer2.3.bn2.weight',\n",
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       " 'module.layer2.3.conv3.weight',\n",
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       " 'module.layer3.2.bn2.num_batches_tracked',\n",
       " 'module.layer3.2.conv3.weight',\n",
       " 'module.layer3.2.bn3.weight',\n",
       " 'module.layer3.2.bn3.bias',\n",
       " 'module.layer3.2.bn3.running_mean',\n",
       " 'module.layer3.2.bn3.running_var',\n",
       " 'module.layer3.2.bn3.num_batches_tracked',\n",
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       " 'module.layer3.3.bn1.weight',\n",
       " 'module.layer3.3.bn1.bias',\n",
       " 'module.layer3.3.bn1.running_mean',\n",
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       " 'module.layer3.3.bn1.num_batches_tracked',\n",
       " 'module.layer3.3.conv2.weight',\n",
       " 'module.layer3.3.bn2.weight',\n",
       " 'module.layer3.3.bn2.bias',\n",
       " 'module.layer3.3.bn2.running_mean',\n",
       " 'module.layer3.3.bn2.running_var',\n",
       " 'module.layer3.3.bn2.num_batches_tracked',\n",
       " 'module.layer3.3.conv3.weight',\n",
       " 'module.layer3.3.bn3.weight',\n",
       " 'module.layer3.3.bn3.bias',\n",
       " 'module.layer3.3.bn3.running_mean',\n",
       " 'module.layer3.3.bn3.running_var',\n",
       " 'module.layer3.3.bn3.num_batches_tracked',\n",
       " 'module.layer3.4.conv1.weight',\n",
       " 'module.layer3.4.bn1.weight',\n",
       " 'module.layer3.4.bn1.bias',\n",
       " 'module.layer3.4.bn1.running_mean',\n",
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       " 'module.layer3.4.conv2.weight',\n",
       " 'module.layer3.4.bn2.weight',\n",
       " 'module.layer3.4.bn2.bias',\n",
       " 'module.layer3.4.bn2.running_mean',\n",
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       " 'module.layer3.4.bn2.num_batches_tracked',\n",
       " 'module.layer3.4.conv3.weight',\n",
       " 'module.layer3.4.bn3.weight',\n",
       " 'module.layer3.4.bn3.bias',\n",
       " 'module.layer3.4.bn3.running_mean',\n",
       " 'module.layer3.4.bn3.running_var',\n",
       " 'module.layer3.4.bn3.num_batches_tracked',\n",
       " 'module.layer3.5.conv1.weight',\n",
       " 'module.layer3.5.bn1.weight',\n",
       " 'module.layer3.5.bn1.bias',\n",
       " 'module.layer3.5.bn1.running_mean',\n",
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       " 'module.layer3.5.bn1.num_batches_tracked',\n",
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       " 'module.layer3.5.bn2.weight',\n",
       " 'module.layer3.5.bn2.bias',\n",
       " 'module.layer3.5.bn2.running_mean',\n",
       " 'module.layer3.5.bn2.running_var',\n",
       " 'module.layer3.5.bn2.num_batches_tracked',\n",
       " 'module.layer3.5.conv3.weight',\n",
       " 'module.layer3.5.bn3.weight',\n",
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       " 'module.layer3.5.bn3.running_var',\n",
       " 'module.layer3.5.bn3.num_batches_tracked',\n",
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       " 'module.dsam_fusion.upscale_3.0.running_var',\n",
       " 'module.dsam_fusion.upscale_3.0.num_batches_tracked',\n",
       " 'module.score_dsn.0.avgpool.conv_layers.0.weight',\n",
       " 'module.score_dsn.0.avgpool.conv_layers.0.bias',\n",
       " 'module.score_dsn.0.avgpool.conv_layers.2.weight',\n",
       " 'module.score_dsn.0.avgpool.conv_layers.2.bias',\n",
       " 'module.score_dsn.0.score_dsn.weight',\n",
       " 'module.score_dsn.0.score_dsn.bias',\n",
       " 'module.score_dsn.0.upscale_.weight',\n",
       " 'module.score_dsn.1.avgpool.conv_layers.0.weight',\n",
       " 'module.score_dsn.1.avgpool.conv_layers.0.bias',\n",
       " 'module.score_dsn.1.avgpool.conv_layers.2.weight',\n",
       " 'module.score_dsn.1.avgpool.conv_layers.2.bias',\n",
       " 'module.score_dsn.1.score_dsn.weight',\n",
       " 'module.score_dsn.1.score_dsn.bias',\n",
       " 'module.score_dsn.1.upscale_.weight',\n",
       " 'module.score_dsn.2.avgpool.conv_layers.0.weight',\n",
       " 'module.score_dsn.2.avgpool.conv_layers.0.bias',\n",
       " 'module.score_dsn.2.avgpool.conv_layers.2.weight',\n",
       " 'module.score_dsn.2.avgpool.conv_layers.2.bias',\n",
       " 'module.score_dsn.2.score_dsn.weight',\n",
       " 'module.score_dsn.2.score_dsn.bias',\n",
       " 'module.score_dsn.2.upscale_.weight',\n",
       " 'module.score_dsn.3.avgpool.conv_layers.0.weight',\n",
       " 'module.score_dsn.3.avgpool.conv_layers.0.bias',\n",
       " 'module.score_dsn.3.avgpool.conv_layers.2.weight',\n",
       " 'module.score_dsn.3.avgpool.conv_layers.2.bias',\n",
       " 'module.score_dsn.3.side_prep.weight',\n",
       " 'module.score_dsn.3.score_dsn.weight',\n",
       " 'module.score_dsn.3.score_dsn.bias',\n",
       " 'module.score_dsn.3.upscale_.weight',\n",
       " 'module.fuse.weight',\n",
       " 'module.fuse.bias',\n",
       " 'module.fuseav.weight',\n",
       " 'module.fuseav.bias',\n",
       " 'module.soundnet8.0.weight',\n",
       " 'module.soundnet8.0.bias',\n",
       " 'module.soundnet8.1.weight',\n",
       " 'module.soundnet8.1.bias',\n",
       " 'module.soundnet8.1.running_mean',\n",
       " 'module.soundnet8.1.running_var',\n",
       " 'module.soundnet8.1.num_batches_tracked',\n",
       " 'module.soundnet8.4.weight',\n",
       " 'module.soundnet8.4.bias',\n",
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       " 'module.soundnet8.8.weight',\n",
       " 'module.soundnet8.8.bias',\n",
       " 'module.soundnet8.9.weight',\n",
       " 'module.soundnet8.9.bias',\n",
       " 'module.soundnet8.9.running_mean',\n",
       " 'module.soundnet8.9.running_var',\n",
       " 'module.soundnet8.9.num_batches_tracked',\n",
       " 'module.soundnet8.11.weight',\n",
       " 'module.soundnet8.11.bias',\n",
       " 'module.soundnet8.12.weight',\n",
       " 'module.soundnet8.12.bias',\n",
       " 'module.soundnet8.12.running_mean',\n",
       " 'module.soundnet8.12.running_var',\n",
       " 'module.soundnet8.12.num_batches_tracked',\n",
       " 'module.soundnet8.14.weight',\n",
       " 'module.soundnet8.14.bias',\n",
       " 'module.soundnet8.15.weight',\n",
       " 'module.soundnet8.15.bias',\n",
       " 'module.soundnet8.15.running_mean',\n",
       " 'module.soundnet8.15.running_var',\n",
       " 'module.soundnet8.15.num_batches_tracked',\n",
       " 'module.soundnet8.18.weight',\n",
       " 'module.soundnet8.18.bias',\n",
       " 'module.soundnet8.19.weight',\n",
       " 'module.soundnet8.19.bias',\n",
       " 'module.soundnet8.19.running_mean',\n",
       " 'module.soundnet8.19.running_var',\n",
       " 'module.soundnet8.19.num_batches_tracked',\n",
       " 'module.soundnet8.21.weight',\n",
       " 'module.soundnet8.21.bias',\n",
       " 'module.soundnet8.22.weight',\n",
       " 'module.soundnet8.22.bias',\n",
       " 'module.soundnet8.22.running_mean',\n",
       " 'module.soundnet8.22.running_var',\n",
       " 'module.soundnet8.22.num_batches_tracked',\n",
       " 'module.fusion3.affine_rgb.weight',\n",
       " 'module.fusion3.affine_rgb.bias',\n",
       " 'module.fusion3.affine_audio.weight',\n",
       " 'module.fusion3.affine_audio.bias',\n",
       " 'module.fusion3.w_a_rgb.weight',\n",
       " 'module.fusion3.w_a_rgb.bias']"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weight_keys"
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  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a.find"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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